mcp template

Local 2025-09-01 01:09:32 0

Developer Tools @o6-webwork/mcp-template

Connects local LLMs to external tools (calculator, knowledge base) via MCP protocol, enabling automatic tool detection and execution to enhance query responses.

Connect your local LLM to real-world tools, knowledge bases, and APIs via MCP.

This project connects a local LLM (e.g. Qwen) to tools such as a calculator or a knowledge base via the MCP protocol. The assistant automatically detects and calls these tools to help answer user queries.

Features

Tool execution through MCP server
Local LLM integration via HTTP or OpenAI SDK
Knowledge base support (data.json)
⚡ Supports stdio and sse transports

Project Files

File	Description
`server.py`	Registers tools and starts MCP server
`client-http.py`	Uses `aiohttp` to communicate with local LLM
`clientopenai.py`	Uses OpenAI-compatible SDK for LLM + tool call logic
`client-stdio.py`	MCP client using stdio
`client-see.py`	MCP client using SSE
`data.json`	Q&A knowledge base

Installation

Requirements

Python 3.8+

Install dependencies:

pip install -r requirements.txt

`requirements.txt`

aiohttp==3.11.18
nest_asyncio==1.6.0
python-dotenv==1.1.0
openai==1.77.0
mcp==1.6.0

Getting Started

1. Run the MCP server

python server.py

This launches your tool server with functions like add, multiply, and get_knowledge_base.

2. Start a client

Option A: HTTP client (local LLM via raw API)

python client-http.py

Option B: OpenAI SDK client

python client-openai.py

Option C: stdio transport

python client-stdio.py

Option D: SSE transport

Make sure server.py sets:

transport = "sse"

Then run:

python client-sse.py

Example Prompts

Math Tool Call

What is 8 times 3?

Response:

Eight times three is 24.

Knowledge Base Question

What are the healthcare benefits available to employees in Singapore?

Response will include the relevant answer from data.json.

Example: `data.json`

[
  {
    "question": "What is Singapore s public holiday schedule?",
    "answer": "Singapore observes several public holidays..."
  },
  {
    "question": "How do I apply for permanent residency in Singapore?",
    "answer": "Submit an online application via the ICA website..."
  }
]

Configuration

Inside client-http.py or clientopenai.py, update the following:

LOCAL_LLM_URL = "..."
TOKEN = "your-api-token"
LOCAL_LLM_MODEL = "your-model"

Make sure your LLM is serving OpenAI-compatible API endpoints.

Cleanup

Clients handle tool calls and responses automatically. You can stop the server or client using Ctrl+C.

License

MIT License. See LICENSE file.